Journal of Combinatorial Optimization - Impact Factor

Journal of Combinatorial Optimization - Springer | 2024 Impact Factor:1.1 | Cite Score:2.6 | Q2

Impact Factor and Journal Rank of Combinatorial Optimization

About: The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational, and applied aspects of combinatorial optimization. It also features reviews of appropriate books and special issues of journals. The objective of the journal is to advance and promote the theory and applications of combinatorial optimization, situated at the intersection of applied mathematics, computer science, and operations research, and overlapping with areas such as computational complexity.
The journal welcomes contributions in the following areas:
Theoretical Aspects: Mathematical foundations, complexity analysis, and structural properties of combinatorial problems.
Computational Techniques: Algorithm design and analysis, computational experiments, and implementation issues.
Applied Studies: Applications in diverse fields including logistics, telecommunications, manufacturing, and bioinformatics.
Interdisciplinary Connections: Contributions that integrate combinatorial optimization with other disciplines like economics, engineering, and biology.
The Journal of Combinatorial Optimization serves as a pivotal platform for researchers and practitioners to disseminate new findings and methodologies, fostering advancements in combinatorial optimization theory and its practical applications.

Journal Home: Journal Homepage

Editor-in-Chief: My T. Thai

Scope: Journal of Combinatorial Optimization is a prominent scholarly journal that publishes high-quality research papers focusing on the theoretical aspects, algorithms, and applications of combinatorial optimization. It serves as a key platform for researchers to exchange ideas and advancements in this critical area of optimization theory. Journal of Combinatorial Optimization publishes innovative research contributions in the following areas:
Theoretical Advances: New theoretical insights and developments in combinatorial optimization, including complexity analysis, approximation algorithms, and exact methods.
Algorithm Design: Development and analysis of algorithms for solving combinatorial optimization problems such as graph theory, network flows, integer programming, and scheduling.
Applications: Real-world applications of combinatorial optimization in various fields such as logistics, telecommunications, manufacturing, and bioinformatics.
Computational Complexity: Studies on the computational complexity of combinatorial problems and the limits of efficient algorithms.
Metaheuristics and Heuristic Methods: Development and evaluation of metaheuristic approaches and heuristic algorithms for combinatorial optimization.
Validation and Rigor: Emphasis on the validation of proposed methods and techniques to ensure scientific rigor and applicability, avoiding articles that propose variants of existing methods without adequate empirical validation.